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IEEE International Conference on Multimedia and Expo (IEEE ICME)

作者： Xue, Jian Zhu, Xiaoye Lu, Ke Kou, Yutong Univ Chinese Acad Sci Beijing 100049 Peoples R China Huazhong Univ Sci & Technol Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9781538692141

The rapid development of graphics hardware has spawned a large number of GPU-based direct volume rendering methods. However, fast volume rendering for out-of-core datasets faces specific challenges, and many in-core-based methods cannot be applied to the volume rendering of out-of-core datasets. Although volume rendering algorithms based on partitioning strategies can effectively overcome these problems, the current partition-based techniques do not achieve a good balance between the partitioning method and the sub-block drawing method. In this paper, we propose an efficient out-of-core volume rendering method for datasets consisting of non-uniform size sub-blocks. The proposed method examines the parallel rendering possibilities between sub-blocks to accelerate the rendering process. Experimental comparisons with several volume rendering algorithms show that our method is faster than the current state-of-the-art approaches.

关键词： out-of-core datasets parallel volume rendering partitioning

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Accelerated composition for parallel volume rendering

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 1998年第1期E81D卷 81-87页

作者： Hirai, T Yamamoto, T Hokkaido Univ Fac Engn Sapporo Hokkaido 060 Japan

We describe an algorithm for efficiently compositing partial images generated during parallel volume rendering on a distributed memory parallel computer. In this object space partitioning algorithm, each PE is assigned to several subvolumes where each subvolume has a corresponding local frame buffer, After volume rendering is performed independently for each subvolume, the partial images stored in the local frame buffers are combined to generate a complete image. During this compositing process, the communication of partial image data between the PEs is kept minimal by assigning PEs to subvolumes in an interleaved manner, This assignment makes possible a reduction in communication in the axis direction in which there is the most communication. Experimental results indicate that a 9% to 35% reduction in the total rendering time can be attained with no additional data structures and no memory overhead.

关键词： medical imaging computer graphics parallel volume rendering compositing distributed memory

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Efficient compositing methods for the sort-last-sparse parallel volume rendering system on distributed memory multicomputers

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JOURNAL OF SUPERCOMPUTING 2001年第2期18卷 201-220页

作者： Yang, DL Yu, JC Chung, YC Feng Chia Univ Dept Informat Engn Taichung 407 Taiwan

In the sort-last-sparse parallel volume rendering system on distributed memory multicomputers, one can achieve a very good performance improvement in the rendering phase by increasing the number of processors. This is because each processor can render images locally without communicating with other processors. However, in the compositing phase, a processor has to exchange local images with other processors. When the number of processors exceeds a threshold, the image compositing time becomes a bottleneck. In this paper, we propose three compositing methods to efficiently reduce the compositing time in parallel volume rendering. They are the binary-swap with bounding rectangle (BSBR) method, the binary-swap with run-length encoding and static load-balancing (BSLC) method, and the binary-swap with bounding rectangle and run-length encoding (BSBRC) method. The proposed methods were implemented on an SP2 parallel machine along with the binary-swap compositing method. The experimental results show that the BSBRC method has the best performance among these four methods.

关键词： sort-last-sparse parallel volume rendering image compositing run-length encoding

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A composition-free parallel volume rendering method

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JOURNAL OF VISUALIZATION 2021年第3期24卷 531-544页

作者： Wang, Jiamin Bi, Chongke Deng, Liang Wang, Fang Liu, Yang Wang, Yueqing Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China China Aerodynam Res & Dev Ctr Computat Aerodynam Inst Mianyang Sichuan Peoples R China

In the in situ visualization of large-scale simulation, if using the traditional sort-last parallel rendering method, the performance cannot be fully improved due to the heavy communication cost in the final stage: compositing of images. In order to resolve this problem, in this paper, we proposed a composition-free parallel volume rendering method. This is achieved by our proposed hybrid parallelization based on the image space partition and octree-based data space partition. Firstly, in the data distribution stage, an octree structure decoupled from volume representation was proposed, which only stored the indicts of sub-blocks, the adjacent sub-blocks, and the space coordinate information of its bounding box. Before rendering, to avoid the compositing stage, a ray-data intersection list was created for each pixel, which sorted by visibility order and identified NON-EMPTY sub-blocks along the ray. Then in the rendering stage, to improve the efficiency of rendering, a ray-data intersection lists-based rendering method was proposed. Finally, we only need to align the partial images to form the final output image. No compositing process is necessary in our parallel volume rendering method. In order to demonstrate the efficiency of our approach, two existing volume rendering methods have been carried out to compare with our composition-free method. Graphic abstract

关键词： parallel volume rendering Compositing-free Octree Ray casting

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Assessing Improvements to the parallel volume rendering Pipeline at Large Scale

Assessing Improvements to the Parallel Volume Rendering Pipe...

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Workshop on Ultrascale Visualization

作者： Peterka, Tom Ross, Robert Yu, Hongfeng Ma, Kwan-Liu Kendall, Wesley Huang, Jian Argonne Natl Lab Argonne IL 60439 USA Sandia Natl Labs Livermore CA 94550 USA Univ Calif Davis Davis CA 95616 USA Univ Tennessee Knoxville TN 37996 USA

ISBN: (纸本)9781424428618

Computational science's march toward the petascale demands innovations in analysis and visualization of the resulting datasets. As scientists generate terabyte and petabyte data, it is insufficient to measure the performance of visual analysis algorithms by rendering speed only, because performance is dominated by data movement. We take a systemwide view in analyzing the performance of software volume rendering on the IBM Blue Gene/P at over 10,000 cores by examining the relative costs of the I/O, rendering, and compositing portions of the volume rendering algorithm. This examination uncovers room for improvement in data input, load balancing, memory usage, image compositing, and image output. We present four improvements to the basic algorithm to address these bottlenecks. We show the benefit of an alternative rendering distribution scheme that improves load balance, and how to scale memory usage so that large data and image sizes do not overload system memory. To improve compositing, we experiment with a hybrid MPI - multithread programming model, and to mitigate the high cost of I/O, we implement multiple parallel pipelines to partially hide the I/O cost when rendering many time steps. Measuring the benefits of these techniques at scale reinforces the conclusion that BG/P is an effective platform for volume rendering of large datasets and that our volume rendering algorithm, enhanced by the techniques presented here, scales to large problem and system sizes.

关键词： parallel volume rendering distributed scientific visualization software raycasting load balancing, scalability, multithreading

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Detail-preserving resampling for parallel volume rendering large unstructured data on earth simulator

Detail-preserving resampling for parallel volume rendering l...

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7th IASTED International Conference on Computer Graphics and Imaging

作者： Chen, L Fujishiro, I Nakajima, K Res Org Informat Sci & Technol Tokyo Japan

ISBN: (纸本)0889864187

A new parallel volume rendering method for large unstructured data has been developed for the Earth Simulator. Concurrent visualization can be performed with numerical computation modules on the supercomputer. The supervoxel partition and voxel resampling techniques were adopted to get high parallel performance for extremely large complicated unstructured datasets. In order to reduce the number of voxels and keep enough precision in the resampling method, a detail-preserving voxel resampling method is presented in which some original unstructured grid elements are added into important voxels. Four kinds of details are defined in the method, including volume, interval, boundary and isosurface details. The implementation and optimization strategies for the Earth Simulator are described according to its hardware architecture. The experimental results show the feasibility and effectiveness of the proposed method.

关键词： distributed visualization parallel volume rendering unstructured grids voxel-based rendering Earth Simulator and performance optimization

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New parallel volume rendering based on shear-wrap using a pipeline framework

New parallel volume rendering based on shear-wrap using a pi...

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Conference on Visual Data Exploration and Analysis IV

作者： Huang, XH Li, W Zheng, NN Xi'an Jiaotong Univ. (China)

ISBN: (纸本)0819424285

In distributed computing environment, an important factor affecting performance of parallel algorithm is communication bandwidth. A new parallel volume rendering algorithm is presented in this paper, based on Shear-Wrap fractorization of the Viewing Transformation using Pipeline Framework of PCs. Taking full use of overlap of communication and computing, we overcome the bottleneck of communication. In the existed algorithms based on object partition, local rendering and image composition are divided into two serial processes. Communication hardly happens during local rendering. In the period of image compositing, however, communication is very busy, and even congested. Furthermore, there are a big synchronism overhead in this period. This paper well solves this drawback by making local rendering and image compositing concurrently through pipeline of PCs. We have experimented on a pipeline composing of 16 Pentiums. The result shows that, performance is not affected much by communication and system overhead is little compared to rendering time. This paper provides a new method for studying on low-price, high-efficiency and real-time volume rendering system.

关键词： distributed parallel volume rendering Shear-Wrap

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DATA-parallel, volume-rendering ALGORITHMS

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VISUAL COMPUTER 1995年第6期11卷 319-338页

作者： YAGEL, R MACHIRAJU, R Department of Computer and Information Science The Ohio State University Columbus USA

In this presentation, we consider the image-composition scheme for parallel volume rendering in which each processor is assigned a portion of the volume. A processor renders its data by using any existing volume-rendering algorithm. We describe one such parallel algorithm that also takes advantage of vector-processing capabilities. The resulting images from all processors are then combined (composited) in visibility order to form the final image. The major advantage of this approach is that, as viewing and shading parameters change, only 2D partial images, and not 3D volume data, are communicated among processors. Through experimental results and performance analysis, we show that our parallel algorithm is amenable to extremely efficient implementations on distributed memory, multiple instruction-multiple data (MIMD), vector-processor architectures. This algorithm is also very suitable for hardware implementation based on image composition architectures. It supports various volume-rendering algorithms, and it can be extended to provide load-balanced execution.

关键词： parallel volume rendering DATA parallel APPROACH COMBINING SPLATTING Z-BUFFER

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Multi-core and many-core shared-memory parallel raycasting volume rendering optimization and tuning

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2012年第4期26卷 399-412页

作者： Bethel, E. Wes Howison, Mark Univ Calif Berkeley Lawrence Berkeley Natl Lab Computat Res Div Sci Visualizat Grp Berkeley CA 94720 USA Brown Univ Ctr Computat & Visualizat Providence RI 02912 USA

Given the computing industry trend of increasing processing capacity by adding more cores to a chip, the focus of this work is tuning the performance of a staple visualization algorithm, raycasting volume rendering, for shared-memory parallelism on multi-core CPUs and many-core GPUs. Our approach is to vary tunable algorithmic settings, along with known algorithmic optimizations and two different memory layouts, and measure performance in terms of absolute runtime and L2 memory cache misses. Our results indicate there is a wide variation in runtime performance on all platforms, as much as 254% for the tunable parameters we test on multi-core CPUs and 265% on many-core GPUs, and the optimal configurations vary across platforms, often in a non-obvious way. For example, our results indicate the optimal configurations on the GPU occur at a crossover point between those that maintain good cache utilization and those that saturate computational throughput. This result is likely to be extremely difficult to predict with an empirical performance model for this particular algorithm because it has an unstructured memory access pattern that varies locally for individual rays and globally for the selected viewpoint. Our results also show that optimal parameters on modern architectures are markedly different from those in previous studies run on older architectures. In addition, given the dramatic performance variation across platforms for both optimal algorithm settings and performance results, there is a clear benefit for production visualization and analysis codes to adopt a strategy for performance optimization through auto-tuning. These benefits will likely become more pronounced in the future as the number of cores per chip and the cost of moving data through the memory hierarchy both increase.

关键词： parallel volume rendering performance optimization auto-tuning multi-core CPU many-core GPU

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An Adaptive Sampling Based parallel volume rendering Algorithm

An Adaptive Sampling Based Parallel Volume Rendering Algorit...

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第十一届中国虚拟现实大会(ICVRV2011)

作者： Huawei Wang Li Xiao Yi Cao High Performance Computing Center Institute of Applied Physics and Computational Mathematics Beijing China

In this paper, a parallel ray-casting volume rendering algorithm based on adaptive sampling is presented for visualizing TB-scale time-varying scientific data. The algorithm samples a data field adaptively according to its inner variation, and thus sets sampling points only in important positions. In order to integrate adaptive sampling into the parallel rendering framework, an efficient method is proposed to handle the resulting unstructured sampling data. The experiments demonstrate that the proposed algorithm can be used to effectively render inner data features in high quality.

关键词： parallel volume rendering adaptive sampling ray casting

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